import pandas as pd
import numpy as np
from pprint import pprint
pd.set_option('display.max_columns', None)

import plotly
plotly.offline.init_notebook_mode()

from sklearn.datasets import load_boston
data = load_boston()
df = pd.concat([pd.DataFrame(data['data'], columns = data['feature_names']), 
                pd.DataFrame(data['target'], columns=['PRICE'])], axis=1)

# Code adopted from 
# https://stackoverflow.com/questions/65881498/plotly-how-to-round-display-text-in-annotated-heatmap-but-keep-full-format-on-h
# by @vestland

import plotly.express as px
import plotly.figure_factory as ff
import pandas as pd
import plotly

#For saving in HTML
plotly.offline.init_notebook_mode()

#Getting Data
dfc = df.corr()
z = dfc.values.tolist()

z_text = [[str(round(y, 2)) for y in x] for x in z]

#Setting up figure 
fig = ff.create_annotated_heatmap(z, 
                                  x=list(df.columns),
                                  y=list(df.columns),
                                  zmax=1,
                                  zmin=-1,
                                  annotation_text=z_text, 
                                  colorscale='Temps')

#Map's Title
fig.update_layout(title_text='Feature Correlation Map\n',
                  #xaxis = dict(title='x'),
                  #yaxis = dict(title='x')
                 )

#Adding xaxis titles
fig.add_annotation(dict(font=dict(color="black",size=14),
                        x=0.5,
                        y=-0.15,
                        showarrow=False,
                        text="",
                        xref="paper",
                        yref="paper"))

#Adding yaxis titles
fig.add_annotation(dict(font=dict(color="black",size=14),
                        x=-0.35,
                        y=0.5,
                        showarrow=False,
                        text="",
                        textangle=-90,
                        xref="paper",
                        yref="paper"))

#Centering a map
fig.update_layout(margin=dict(t=75), height=850, width=850)
#Adding a colorbar
fig['data'][0]['showscale'] = True
fig.show()